Authors:
,
,
, and
Z. Nazari
Z. Nazari
Quantitative Plant Ecology and Biodiversity Research Lab, Department of Biology Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
Search for other papers by Z. Nazari in
Current site
Google Scholar
PubMed
Search for other papers by Z. Nazari in
Current site
Google Scholar
PubMed
H. Ejtehadi
hejtehadi@um.ac.ir
H. Ejtehadi
Quantitative Plant Ecology and Biodiversity Research Lab, Department of Biology Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
Search for other papers by H. Ejtehadi in
Current site
Google Scholar
PubMed
Search for other papers by H. Ejtehadi in
Current site
Google Scholar
PubMed
O. Mirshamsi
O. Mirshamsi
Institute of Applied Zoology (RDZI), Faculty of Science Ferdowsi University of Mashhad, Mashhad, Iran
Department of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
Search for other papers by O. Mirshamsi in
Current site
Google Scholar
PubMed
Department of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
Search for other papers by O. Mirshamsi in
Current site
Google Scholar
PubMed
F. Memariani
F. Memariani
Herbarium FUMH, Department of Botany, Research Centre for Plant Science Ferdowsi University of Mashhad, Mashhad, Iran
Search for other papers by F. Memariani in
Current site
Google Scholar
PubMed
Search for other papers by F. Memariani in
Current site
Google Scholar
PubMed
Ferula microcolea (Boiss.) Boiss. is an endemic plant in Iran that some of its habitats have been destroyed in recent decades. Since the bioclimatic variables which determine its potential distribution, are poorly defined, a specific analysis is needed. In this study, the species distribution modelling was used for reaching these goals: (i) identifying the bioclimatic factors that constrain the distribution of this species in Iran, (ii) generating a potential habitat suitability map for F. microcolea using Maxent (iii) determining the high suitable areas where this species could be present (iv) evaluating the final model. In all, 66 records of F. microcolea in Iran were used as the occurrence data. Nineteen bioclimatic variables were obtained from the WorldClim database and collinear variables were removed in a sequential manner with regard to the ecological knowledge of the plant. The maxent parameters were optimised with ENMeval R package. For evaluating the performance of the Maxent model, the Area under curve value (AUC) was calculated. The results showed that the model performance was excellent. Analysis of variable contribution demonstrated that the distribution of this species is most influenced by the Annual Mean Temperature. We revealed that the area about 22,005.5 km2 is highly suitable for F. microcolea that is principally located in Chaharmahal and Bakhtiari province. Although this region is rich in biodiversity, greater focus should be paid to its conservation. Our findings provide a scientific basis for the habitats conservation of this species in Iran.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
Amiri, H. (2014): Chemical composition and antioxidant activity of essential oil and methanolic extracts of Ferula microcolea (Boiss.) Boiss (Apiaceae). –Int. J. Food Prop. 17(4): 722–730.
-
Anderson, R. P. and Gonzalez, I. (2011): Species-specific tuning increases robustness to sampling bias in models of species distributions: an implementation with Maxent. –Ecol. Model. 222(15): 2796–2811.
-
Anderson, S. (1994): Area and endemism. –Quart. Rev. Biol. 69(4): 451–471.
-
Ashcroft, M. B., Gollan, J. R., Warton, D. I. and Ramp, D. (2012): A novel approach to quantify and locate potential microrefugia using topoclimate, climate stability, and isolation from the matrix.–Global Change Biol. 18: 1866–1879.
-
Austin, M. P. (2002): Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. –Ecol. Model. 157(2–3): 101–118.
-
Bai, D.-F., Chen, P.-J., Atzeni, L., Cering, L., Li, Q. and Shi, K. (2018): Assessment of habitat suitability of the snow leopard (Panthera uncia) in Qomolangma National Nature Reserve based on MaxEnt modeling. –Zool. Res. 39(6): 373–386.
-
Block, W. M. and Brennan, L. A. (1993): The habitat concept in ornithology. Theory and applications. Springer, Boston, MA.–Current Ornithology 11: 35–91.
-
Boissier, E. (1872): Flora orientalis.–Genevae & Basileae, 2: 574–582.
-
Bucklin, D. N., Basille, M., Benscoter, A. M., Brandt, L. A., Mazzotti, F. J., Romañach, S. S., Speroterra, C. and Watling, J. I. (2015): Comparing species distribution models constructed with different subsets of environmental predictors. –Divers. Distrib. 21(1): 23–35.
-
Chamberlain, D. F. and Rechinger, K. H. (1987): Ferula. – In: Rechinger, K. H. (ed.): Flora Iranica 162: 387–426.
-
Chang, Y. L., Xia, Y., Peng, M. W., Chu, G. M. and Wang, M. (2020): Maxent modelling for predicting impacts of climate change on the potential distribution of Anabasis aphylla in northwestern China. –Appl. Ecol. Env. Res. 18: 1637–1648.
-
Convertino, M., Muñoz-Carpena, R., Chu-Agor, M. L., Kiker, G. A. and Linkov, I. (2014): Untangling drivers of species distributions: global sensitivity and uncertainty analyses of MaxEnt. –Environ. Model. Softw. 51: 296–309.
-
Daneshvar, M. R. M., Ebrahimi, M. and Nejadsoleymani, H. (2019): An overview of climate change in Iran: facts and statistics. –Environ. Syst. Res. 8(1): 7.
-
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., García Marquéz, J. R., Gruber, B., Lafourcade, B., Leitao, P. J., Münkemüller, T., McClean, C., Osborne, P. E., Reineking, B., Schröder, B., Skidmore, A. K., Zurell, D. and Lautenbach, S. (2013): Col-linearity: a review of methods to deal with it and a simulation study evaluating their performance. –Ecography 36(1): 27–46.
-
Dubuis, A., Giovanettina, S., Pellissier, L., Pottier, J., Vittoz, P. and Guisan, A. (2013): Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variable. –J. Veg. Sci. 24: 593–606.
-
Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E. and Yates, C. J. (2011): A statistical explanation of Maxent for ecologists. –Divers. Distrib. 17(1): 43–57.
-
Feng, X., Gebresenbet, F. and Walker, C. (2017): Shifting from closed-source graphical-interface to open-source programming environment: a brief tutorial on running Maxent in R.–PeerJ Preprints 5: e3346v1.
-
Franklin, J. (2010): Mapping species distributions: spatial inference and prediction. – Cambridge University Press, Cambridge.
-
Galante, P. J., Alade, B., Muscarella, R., Jansa, S. A., Goodman, S. M. and Anderson, R. P. (2018): The challenge of modeling niches and distributions for data-poor species: a comprehensive approach to model complexity. –Ecography 41(5): 726–736.
-
Ghazimoradi, L., Tarkesh, M., Bashari, H. and Wahhabi, M. R. (2016): Determination of potential habitat of Ferula ovina Boiss. using generalized additive model (GAM) in Fereidunshahr area of Isfahan province.–Rangeland and Watershed Management 69(3): 677–689.
-
Guisan, A. and Zimmermann, N. E. (2000): Predictive habitat distribution models in ecology. –Ecol. Model. 135(2–3): 147–186.
-
Henderson, E. B., Ohmann, J. L., Gregory, M. J., Roberts, H. M. and Zald, H. (2014): Species distribution modelling for plant communities: stacked single species or multivariate modelling approaches?– Appl. Veg. Sci. 17(3): 516–527.
-
Hernandez, P. A., Graham, C. H., Master, L. L. and Albert, D. L. (2006): The effect of sample size and species characteristics on performance of different species distribution modeling methods. –Ecography 29(5): 773–785.
-
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. and Jarvis, A. (2005): Very high resolution interpolated climate surfaces for global land areas. –Int. J. Climat. 25(15): 1965–1978.
-
Hijmans, R. J., Etten, J. V., Cheng, J., Sumner, M., Mattiuzzi, M. Greenberg, J. A. and Lamigueiro, O. P. (2015): Package ‘raster’. – R package version 2.5-8.
-
Jalili, A. and Jamzad, Z. (1999): Red Data Book of Iran, a preliminary survey of endemic, rare & endangered plant species in Iran. – Research Institute of Forest & Rangelands, Ministry of Jahad-e Sazandegi (Publ. 215), 748 pp.
-
Kaky, E. and Gilbert, F. (2019): Assessment of the extinction risks of medicinal plants in Egypt under climate change by integrating species distribution models and IUCN Red List criteria. –J. Arid Environ. 170, Art. 103988.
-
Kalinski, C. E. (2019): Building better species distribution models with machine learning: assessing the role of covariate scale and tuning in Maxent models. – Doctoral dissertation, University of Southern California.
-
Khalaj, A. and Mortazavi, S. M. (2016): Climatic zoning of precipitation and temperature in Chaharmahal and Bakhtiari Province using geographic information system (GIS). –Res. J. Appl. Sci. 11(7): 496–507.
-
Li, J., Fan, G. and He, Y. (2020): Predicting the current and future distribution of three Coptis herbs in China under climate change conditions, using the Max-Ent model and chemical analysis. –Sci. Total Environm. 698: 134–141.
-
Mazangi, A., Ejtehadi, H. and Mirshamsi, O., Ghassemzadeh, F. and Hosseinianyou sefkhani, S. S. (2016): Effects of climate change on the distribution of endemic Ferula xylorhachis Rech. f. (Apiaceae: Scandi ceae) in Iran: Predictions from ecological niche models. –Russ. J. Ecol. 47: 349–354.
-
Mozaffarian, V. (1983): The family of Umbelliferae in Iran. –Pub. Res. Inst. Forest Rangelands 35: 146–147.
-
Mozaffarian, V. (1996): A dictionary of Iranian plant names. – Farhang Moaser, Tehran, 396 pp.
-
Mozaffarian, V. (2007): Umbelliferae. – In: Assadi, M. et al. (eds): Flora of Iran. Vol. 54. Research Institute of Forests and Rangelands, Tehran, pp. 280–296.
-
Muscarella, R., Galante, P. J., Soley-Guardia, M., Boria, R. A., Kass, J. M., Uriarte, M. and Anderson, R. P. (2014): ENMeval: an R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. –Methods Ecol.Evol. 5(11): 1198–1205.
-
Naimi, B. (2015): Usdm: Uncertainty analysis for species distribution models.–R package version, 1, 1–12.
-
Noroozi, J., Akhani, H. and Breckle, S. W. (2008): Biodiversity and phytogeography of the alpine flora of Iran. –Biodiv. Conserv. 17(3): 493–521.
-
Peterson, A. T., Papeş, M. and Soberón, J. (2008): Rethinking receiver operating characteristic analysis applications in ecological niche modelling. –Ecol. Model. 213(1): 63–72.
-
Phillips, S. J. and Dudík, M. (2008): Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. –Ecography 31(2): 161–175.
-
Phillips, S. J., Anderson, R. P. and Schapire, R. E. (2006): Maximum entropy modeling of species geographic distributions. –Ecol. Model. 190(3–4): 231–259.
-
Pimenov, M. G. and Leonov, M. V. (2004): The Asian Umbelliferae biodiversity database (ASIUM) with particular reference to South-West Asian taxa. –Turkish J.Bot. 28(1–2): 139–145.
-
Pradhan, P. (2016): Strengthening MaxEnt modelling through screening of redundant explanatory bioclimatic variables with variance inflation factor analysis. –Researcher 8(5): 29–34.
-
Razmi, R., Balyani, S. and Daneshvar, M. R. M. (2017): Geo-statistical modeling of mean annual rainfall over the Iran using ECMWF database. –Spat. Inf. Res. 25(2): 219–227.
-
Saadatfar, A., Tavassolian, I. and Jafari, S. H. (2018): Determining the potential habitat of Ferula assafoetida using hierarchical analysis and geographic information system (Case study: Chatroud region, Kerman).–RS & GIS for Nat. Res. 9(4): 139–155.
-
Safaian, N. and Shokri, M. (1992): Botanical and ecological study of species of the genus Ferula (Medicinal Plants) in Mazandaran province.–WOCMAP I. Medicinal and Aromatic Plants Conference (ISHS 333), pp. 159–164.
-
Sahebkar, A. and Iranshahi, M. (2010): Biological activities of essential oils from the genus Ferula (Apiaceae).–Asian Biomed. 4(6): 835–847.
-
Sony, R. K., Sen, S., Kumar, S., Sen, M. and Jayahari, K. M. (2018): Niche models inform the effects of climate change on the endangered Nilgiri Tahr (Nilgiritragus hylocrius) populations in the southern Western Ghats, India.–Ecol. Engineer. 120: 355–363.
-
Sharifi, Y. M., Shahmoradi, A. and Zare, K. (2014): Ecological study of Ferula ovina Boiss in Kerman province. –Renew. Nat. Resour. Res. 5(2): 57–68.
-
Urbani, F., D’Alessandro, P. and Biondi, M. (2017): Using Maximum Entropy Modeling (MaxEnt) to predict future trends in the distribution of high altitude endemic insects in response to climate change. –B. Insectol. 70(2): 189–200.
-
Valenzuela-Ceballos, S., Castañeda, G., Rioja-Paradela, T., Carrillo-Reyes, A. and Bastiaans, E. (2015): Variation in the thermal ecology of an endemic iguana from Mexico reduces its vulnerability to global warming. –J. Therm. Biol. 48: 56–64.
-
Wang, J., Liu, H., Li, Y. and Zhang, H. (2019): Habitat quality of overwintering red-crowned cranes based on ecological niche modeling. –Arab. J. Geosci. 12(24), 750.
-
Warren, D. L. and Seifert, S. N. (2011): Ecological niche modeling in Maxent: The importance of model complexity and the performance of model selection criteria. –Ecol. Appl. 21(2): 335–342.
-
Wei, B., Wang, R., Hou, K., Wang, X. and Wu, W. (2018): Predicting the current and future cultivation regions of Carthamus tinctorius L. using MaxEnt model under climate change in China. –Global Ecol.Conserv. 16: e00477.
-
Zhang, J., Jiang, F., Li, G., Qin, W., Li, S., Gao, H., Cai, Z., Lin, G. and Zhang, T. (2019): Maxent modeling for predicting the spatial distribution of three raptors in the Sanjiangyuan National Park, China.–Ecol. Evol. 9(11): 6643–6654.
Botta-Dukát, Zoltán
E-mail: botta-dukat.zoltan@okologia.mta.hu
or
Lőkös, László
E-mail: acta@bot.nhmus.hu
Institute: Botanical Department, Hungarian Natural History Museum
Address: Könyves K. krt. 40. H-1097 Budapest, Hungary
- Scopus
- Biological Abstracts
- BIOSIS Previews
- CAB Abstracts
- CABELLS Journalytics
- Chemical Abstracts
- Global Health
- Referativnyi Zhurnal
| 2023 | |
|---|---|
| Scopus | |
| CiteScore | 1.7 |
| CiteScore rank | Q3 (Plant Science) |
| SNIP | 0.749 |
| Scimago | |
| SJR index | 0.24 |
| SJR Q rank | Q3 |
| Acta Botanica Hungarica | |
|---|---|
| Publication Model | Hybrid |
| Submission Fee | none |
| Article Processing Charge | 900 EUR/article (only for OA publications) |
| Printed Color Illustrations | 40 EUR (or 10 000 HUF) + VAT / piece |
| Regional discounts on country of the funding agency | World Bank Lower-middle-income economies: 50% World Bank Low-income economies: 100% |
| Further Discounts | Editorial Board / Advisory Board members: 50% Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100% |
| Subscription fee 2025 | Online subsscription: 696 EUR / 764 USD Print + online subscription: 788 EUR / 868 USD |
| Subscription Information | Online subscribers are entitled access to all back issues published by Akadémiai Kiadó for each title for the duration of the subscription, as well as Online First content for the subscribed content. |
| Purchase per Title | Individual articles are sold on the displayed price. |
| Acta Botanica Hungarica | |
|---|---|
| Language | English French German Russian Spanish |
| Size | B5 |
| Year of Foundation |
1954 |
| Volumes per Year |
1 |
| Issues per Year |
4 |
| Founder | Magyar Tudományos Akadémia |
| Founder's Address |
H-1051 Budapest, Hungary, Széchenyi István tér 9. |
| Publisher | Akadémiai Kiadó |
| Publisher's Address |
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245. |
| Responsible Publisher |
Chief Executive Officer, Akadémiai Kiadó |
| ISSN | 0236-6495 (Print) |
| ISSN | 1588-2578 (Online) |
Monthly Content Usage
| Abstract Views | Full Text Views | PDF Downloads | |
|---|---|---|---|
| Oct 2024 | 122 | 1 | 1 |
| Nov 2024 | 57 | 0 | 0 |
| Dec 2024 | 51 | 0 | 0 |
| Jan 2025 | 67 | 0 | 0 |
| Feb 2025 | 75 | 0 | 0 |
| Mar 2025 | 67 | 0 | 0 |
| Apr 2025 | 0 | 0 | 0 |
Author:
Authors:
, , , , , , , and
Author:
Authors:
, , , , , , , , , , , , , , and
Copyright Akadémiai Kiadó AKJournals is the trademark of Akadémiai Kiadó's journal publishing business branch.
Powered by PubFactory